一种用于碳排放预测的新型综合优化模型:对20人组的案例研究
Yidong Zhang1, Xiong Li1, Yiwei Zhang2
1School of Systems Science and Engineering, Sun Yat-sen University, Guangzhou, Guangdong, 510006, China.
Journal of environmental management
|June 29, 2023
概括
准确的碳排放预测对于环境政策至关重要. 本研究引入了一种新型模型,集成时间序列和影响因素,提高有效的碳减排策略的预测准确度.
科学领域:
- 环境科学 环境科学
- 气候变化研究 气候变化研究
- 计量经济学 计量经济学 计量经济学
背景情况:
- 碳排放是温室效应和环境政策的核心.
- 现有的模型缺乏时间序列预测和影响因素分析的整合.
- 有效的碳减排政策需要强大的预测模型.
研究的目的:
- 开发一个全面的碳排放预测模型.
- 将时间序列分析与使用既定经济理论的影响因素结合起来.
- 为碳减排政策提供科学指导.
主要方法:
- 用环境库兹涅茨曲线 (EKC) 理论进行定性分析.
- 开发了一个集成模型 (SSA-FAGM-SVR),结合了搜索算法 (SSA),分数积累灰色模型 (FAGM) 和支持向量回归 (SVR).
- 应用该模型来预测G20未来十年的碳排放.
主要成果:
- 通过SSA-FAGM-SVR模型,预测准确度显著提高.
- 该模型在预测碳排放方面表现出强大的适应性和高精度.
- 在准确性和可靠性方面超过了其他主流预测算法.
结论:
- 拟议的综合模型为碳排放预测提供了一种优越的方法.
- 该方法为实施有效的碳减排政策提供了有价值的科学指导.
- 该模型的准确性和适应性支持其在环境政策制定中的应用.
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